ConQuR-Bio: Consensus Ranking with Query Reformulation for Biological Data

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• 作者：Bryan Brancotte (20) (21)
  Bastien Rance (23) (24)
  Alain Denise (20) (21) (22)
  Sarah Cohen-Boulakia (20) (21)
  
• 刊名：Lecture Notes in Computer Science
• 出版年：2014
• 出版时间：2014
• 年：2014
• 卷：8574
• 期：1
• 页码：128-142
• 全文大小：1,380 KB
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• 作者单位：Bryan Brancotte (20) (21)
  Bastien Rance (23) (24)
  Alain Denise (20) (21) (22)
  Sarah Cohen-Boulakia (20) (21)
  
  20. Laboratoire de Recherche en Informatique (LRI), CNRS UMR 8623, Universit茅 Paris-Sud, 91405, Orsay Cedex, France
  21. AMIB Group, INRIA Saclay Ile-de-France, France
  23. Biomedical Informatics and Public Health Department, University Hospital Georges Pompidou, AP-HP, Paris, France
  24. INSERM Centre de Recherche des Cordeliers, team 22: Information Sciences to support Personalized Medicine, Universit茅 Paris Descartes, Sorbonne Paris Cit茅, Facult茅 de m茅decine, Paris, France
  22. Institut de G茅n茅tique et de Microbiologie (IGM), CNRS UMR 8621, Universit茅 Paris-Sud, France
  
• ISSN：1611-3349

文摘

This paper introduces ConQuR-Bio which aims at assisting scientists when they query public biological databases. Various reformulations of the user query are generated using medical terminologies. Such alternative reformulations are then used to rank the query results using a new consensus ranking strategy. The originality of our approach thus lies in using consensus ranking techniques within the context of query reformulation. The ConQuR-Bio system is able to query the EntrezGene NCBI database. Our experiments demonstrate the benefit of using ConQuR-Bio compared to what is currently provided to users. ConQuR-Bio is available to the bioinformatics community at http://conqur-bio.lri.fr .